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HEALTHCARE AND LIFE SCIENCES

Predictive analytics and machine learning are rapidly gaining traction in the healthcare and life sciences industry. Healthcare can be made more proactive through the utility of predictive analytics for improving patient care, prolonged disease management, hospital administration, and to overcome supply chain inefficiencies. The industry is lately getting overloaded with data, majorly from the patient, clinical, claim, hospital system, financial, pharmacy, and from wearable technology sources. The industry is pushing towards generating electronic health records and periodically updating reporting methods and data storage with the advent of advanced analytical technologies for decision-making.

In healthcare, the prediction is most useful when gathered insights can be utilized into action. Hence, with the on-going development of predictive analytics software, healthcare providers are adopting the predictive analytics solutions. According to a survey carried by Society of Actuaries (SOA), a professional organization for actuaries based in North America, around 47% of the providers use predictive analytics.

Additionally, owing to the worldwide adoption of electronic health records, large healthcare institutions, and healthcare systems have begun to recognize analytics as mean to predict future and has relied on the capabilities to bring patients trends and patterns. The real-time EHR data analytics helped a hospital located in Texas, US to cut the patient readmission by 5%, indicating the importance of real-time analytics in the healthcare industry. Predictive analytics solutions enable organizations to consolidate data at a centralized location, categorize it, and maintain it in an easy way to understand format resulting in enhanced customer experience.

Moreover, the Veteran’s Health Administration (VHA) accumulated over 30 years of electronic patient data, which later, post building a data warehouse and developing predictive algorithms that are able to predict health and death risks, it used this data to enhance its efficiency while improving the quality of patient care. This lead VHA to receive a net benefit of USD 3 billion through predictive analytics.

COMPETITIVE LEADERSHIP MAPPING TERMINOLOGY

The Healthcare and Life Sciences predictive analytics software vendors are placed into 4 categories based on their performance in each criterion: “visionary leaders,” “innovators,” “dynamic differentiators,” and “emerging companies.” The top 23 vendors evaluated in the data quality tools market include Agilone, Alteryx, Inc, Angoss Software Corporation, Dataiku, Domino, Data Lab, Exago, Inc., Fair Isaac Corporation (Fico), Good Data, IBM Corporation, Information Builders, Inc., Knime Ag, Microsoft Corporation, Microstrategy Incorporated, NTT Data Corporation, Oracle Corporation, Qliktech, Inc., Rapidminer, Inc, SAP SE, SAS Institute Inc, Sisense, Tableau Software Inc, Teradata Corporation, and Tibco Software Inc.

Use Cases of Predictive Analytics software in Healthcare and Life Sciences

  • Risk Scoring for Chronic Diseases, Population Health: Creating risk scores based on lab testing, biometric data, claims data, patient-generated health data and the social determinants of health provide healthcare providers insight into individuals so that they benefit from enhanced services
  • Getting Ahead of Patient Deterioration: Data analytics can help providers react as quickly as possible to changes in a patient’s vitals and able to identify an upcoming deterioration before symptoms are clearly visible to the naked eye
  • Preventing Suicide and Patient Self-Harm: EHRs can support suicide risk detection using a predictive algorithm
  • Predicting Patient Utilization Patterns: Using analytics to predict patterns in utilization can help ensure optimal staffing levels while reducing waiting times. Visualization tools and analytics can model patient flow patterns and highlight opportunities to make workflow adjustments or changes
  • Supply Chain Management: Predictive tools can help hospital executives gain more actionable insights into ordering patterns and supply utilization

Developing Precision Medicine and New Therapies: Predictive analytics and clinical decision support tools are used in translating new drugs into precision therapies. Tools are able to predict a patient’s response to a certain course of treatment by matching genetic information with the results from previous patient cohorts, allowing providers to choose the most likelihood therapy


Case Studies of Predictive Analytics Software in Healthcare and Life Science

 

Cerner Corporation

Case Stuy: Advocate Health Care lowers readmissions with Cerner’s predictive analytics solution

Advocate Health Care partnered with Cerner and created Advocate Cerner Collaborative (ACC) in 2012. Since then both organizations have worked together to develop advanced, evidence-based analytics to improve the quality of patient care

Business Outcome:

  • Patients who received high risk education using Cerner solutions had a 20% lower readmission rate

 

Epic Systems

Case Study: At Bellin Health, Epic system’s teamwork was used for patient care. When a patient’s physician asks about his/her health, a nurse or other member of the care team uses Teamwork to quickly review and address all the care related gaps

Business Outcome:

  • Bellin’s comprehensive approach to each patient’s care helped keep its patients healthy due to which 75% of all visits at Bellin Health in 2018 were regular wellness visits
  • This focus on wellness helped Bellin Health achieve top performance in the Next Generation ACO program

 

Clarify Health Solutions:

Case Study: John Muir Health, located in San Francisco Bay Area, was struggling to manage value-based programs in the dark, without the evidence to inform and support decisions.

Clarify’s solution provides the health system with the critical analytical foundation for their bundled payments program. It delivers the actionable insights needed to succeed in the CJR program.

Business Outcome:

  • John Muir Health’s system scored an excellent rating on quality
  • Captured USD 1,900 per episode in bonus in the first year of the CJR program

 

Qventus:

Case Studuy: Natividad Medical Center, a 172-bed acute care hospital located in Salinas, California, faced issues regarding Data transparency and Real-time data visualization.

To help frontline care staff prioritize their concurrent tasks, Qventus gave nurses actionable nudge to focus on actions that would directly impact patient flow. The system is able to predict issues before they occur and prescribe actions which should be immediately taken to go ahead

Business Outcome:

  • Average LWBS rate dropped 42%, shedding 1.6 percentage points using 18 months of data
  • Average admitted patients LOS dropped 30 minutes, an 8% reduction
  • Door-to-doc time shortened by 10 minutes, a 20% reduction
  • Provide an estimated 850 additional visits yearly with a projected $425,000 in additional revenue

IBM Corporation

Case Study: Health Quest, a non-profit, four-hospital health system with locations in Connecticut and New York’s Hudson Valley, needed access to real-time patient data to meet quality-based performance benchmarks.

 

Health Quest was able to identify gaps, track individual touch points and refine its care process to improve system-wide population health

Business Outcome:

  • Health Quest generated USD 3.7 million in total billing revenue
  • Received a final MIPS score of 93.32 out of 100 resulting in a 1.65 percent payment bonus in year 1 and met the care management requirements of CPC+ Track 2

 

Leidos

Case Study: Leidos and the University of Miami Health System have worked together on a predictive analytics solution that can deliver data to physicians wherever they need it, enabling them to make informed decisions at the point of care. The doctor can see the system's recommendations on the screen and can take immediate action during the consultation.

Business Outcome:

  • Elaborated a potential cost saving of up to USD 12.5 million as pre-diabetic patients are successfully identified and put through diabetes prevention training

 

AllScripts:

Case Studies:Fraser Health Authority, Canada is using AllScripts’ DbMotion clinical analytics which enables clinicians to examine wider caseloads than they have in their own practices and making information available within the clinician workflow

Business Outcome:

  • It helped Fraser Health standardize processes ahead of time and prepare with extensive testing, particularly for data validation before going live

 

Health Catalyst:

Case Study: Employer Health Plan successfully lowers costs and boosts benefits. Health Catalyst decided to embrace self-insurance to take the management of its healthcare costs and benefit design into its own hands as well as gain access to the data it needed to manage its population health.

The organization is currently leveraging data and analytics to help uncover insights into improvement opportunities and methods to drive behavior change in its team member

Business Outcome:

  • Successfully moved from a unmanaged organization to a self-insured/managed organization in less than five years
  • Re-invested cost savings into enhancing employee benefits

 

CitiusTech:

Case Study: Predicting High-risk Chronic Kidney Disease (CKD) Patients. Medictiv team of CitiusTech identified key analytics features required by nephrologists, built a technological roadmap for analytics, implemented data cleansing, transformation and quality checks to build data confidence

Business Outcome:

  • Developed and validated clinical models with accuracy upto 74%
  • Developed real-time score cards to track data quality, cleanse and profile data for different use cases

 

Inovalon:

Case Study: Inovalon deployed a strategy that included direct mail, telephonic communications and appointment reminders via SMS text message to the payer’s commercial patients which were identified as possible care gaps.

The goal was to improve overall health outcomes for the patient population while driving efficiencies and improving financial performance through multiple channels

Business Outcome:

  • National Healthcare payer increases patient intervention completion rate by 73% with 55% fewer program eligible patients

McKesson:

Case Study: Biopharma Companies’ Real-time data were collected daily from community oncology practices across the country representing thousands of physicians.

To successfully introduce new therapies and support long-term commercial needs, biopharma companies required a deep understanding of disease landscapes so that they must be able to quickly identify the patient population, understand patterns of care and develop a plan to deliver appropriate clinical education and messaging to physicians in order to help them make the most favorable clinical decisions for their patients

Business Outcome:

  • McKesson’s comprehensive data analytics model collected structured clinical data from more than 2,200 providers and 650 sites of care across the U.S and took timely actions

 

MedeAnalytics:

Case Study: Adventist Health, a non-profit healthcare provider based in California, used MedeAnalytics Patient Access across its 19 hospitals to increase point-of-service collections, patient experience, and streamline patient registration workflows

Business Outcome:

  • Adventist Health boosted point-of-service collections by $3.8 million over two years, representing a 20% increase across the organization

NextHealth Technologies:

Case Study: Randomized trial in Oregon showed that expanding Medicaid coverage increased emergency department (ED) use by 40% including visits for conditions that might best be treated by a primary care physician.

NextNudge, which uses machine-learning techniques, was used to identify members to nudge such as relatively healthy members with no recent wellness visits but with a history of recent ED use and to track the results of nudging them

Business Outcome:

  • 25% Reduction in Avoidable Emergency Room Visits

NOUS Infosystems:

Case Study: A Health informatics company required a sophisticated and flexible system with a Business Intelligence dash board and reporting solution having Data Visualization features which enables access to real-time actionable information on spends and performance

Business Outcome:

  • Better visibility on spends to optimize the procedure and reduce cost
  • Improved decision making on health insurance plans with reduced assumptions

Flatiron Health:

Case Study: Flatiron Health is using data and analytics to tackle cancer. Flatiron’s goal is to accelerate cancer research and improve patient care by enabling cancer researchers and care providers to leverage its analytics software platform and learn from the experience of each patient to enhance the development of new treatments

Business Outcome:

  • Flatiron platform helped in identifying right patient cohorts for almost 15 types of cancer conditions for clinical trials, thereby optimizing clinical trial enrollment

 

SAS:

Case Study: Competitive Health Analytics (CHA), a Humana company that provides research and analytics services to the pharmaceutical and health care industries used SAS Health Analytics to perform comparative effectiveness studies, drug safety analysis and subgroup analysis to find drugs that work particularly well in certain types of patients

 Business Outcome:

  • Using SAS, Competitive Health Analytics grew business by 50% in one year

 

Amitech:

Case Study: Amitech worked with a Healthcare provider to develop a breakthrough mHealth platform that leverages near real-time streaming data, psychographic user profiles and a predictive analytics engine to offer users important insights and personalized nudge suggestions

Business Outcome:

  • Participants in an initial pilot program increased activity by 11% and total hours slept by 17%
  • First-gen platform was able to reduce claims within 6 weeks of implementation with a USD 15 million reduction in cost of care in first year

 

Conifer Health Solutions:

Case Study: KentuckyOne Health Partners turned to Conifer Health Solutions to help guide its care managers for positive outcomes. Conifer Health’s Population Health Intelligence platform manages the 1,00,000 lives by capturing enrollment, claims and clinical data to stratify and identify high-risk populations

Business Outcome:

  • Improved quality and patient satisfaction resulting in more than USD 27 million in Medicare shared savings over the past three years

OPTUM One:

Case Study: Using Optum One, data and analytics platform, UMass combined patient information from two separate electronic medical records. Data was blended with historic patient care registry information and claims data from five payers to identify gaps in adult immunizations for flu and pneumonia

Business Outcome:

  • Increased pneumonia immunization rates for Medicare patients by 17.4 percent
  • Improved communication with physicians using transparent data and analytic sharing

 

AETION:

Case Study: Rutgers Ernest Mario School of Pharmacy used Aetion Evidence Platform for collaborative, transformative generation of essential evidence at scale. Analytics platform addressed the growing need for timely, consistent and reproducible real-world evidence where data can be obtained from any sources

Business Outcome:

  • Fully causal, risk-adjusted assessments
  • Real-time collaboration among parties
  • “Time to evidence” reduced to near real-time

 

Zephyr Health:

Case Study: A global life sciences company was trying to get a new therapy for multiple sclerosis (MS). The therapy was in development for use in an autoimmune disorder but fell short in clinical trials.

Zephyr Health was brought in to investigate the problem and check why providers were not relevant and what, if any, changes could be made to improve the output

Business Outcome:

  • Zephyr Health’s solution reduced the number of irrelevant key opinion leaders from 51% to under 20%
  • Medical Science Liaisons team was able to operate 10% faster

 

EVIDATION HEALTH:

Case Study: Stanford Biodesign was searching for a technology platform that can enable companies to accurately quantify the value of their health-related technologies outside of clinic walls.

Evidation Health demonstrated their value and product market fit in such condition

Business Outcome:

  • Evidation received a DARPA grant to execute a virtual RCT in over 75,000 patients with the goal of understanding how mobile-based interventions could impact US flu vaccination rates

 

Greenway Health:

Case Study: Northwest Primary Care involved in value-based care through Medicare Advantage plans. To meet clinical and financial targets, Northwest Primary Care relied on a care team that is integrated through technology and manages patients using strategies that mitigate clinical risk

Business Outcome:

  • Improved Care coordination to minimize hospitalizations
  • Provided proactive approach to value-based care

 

IMAT Solutions:

Case Study: Healthcare Access San Antonio (HASA), the non-profit community, needed enhancements in its master patient index (MPI) capability and comprehensive reporting efforts. It also required a more robust data warehousing solution and the ability to identify gaps in both unrecognized and unleveraged data

Business Outcome:

  • Allowed HASA to liberate the data for smaller providers who now have a full picture of their patients through the IMAT platform
  • Reduced penalties for not meeting the 30-day risk standardized readmission measures

 

Acmeware:

Case Study: Chinook Health, part of Alberta Health Services, was facing issues in the pending retirement of their MAGIC system. Several options were considered to preserve the historical MAGIC data, but did not have any of the non-converted historical data. Acmeware helped in finding solution here

Business Outcome:

  • Unavailable historical data from a soon-to-be retired MAGIC system allowed the preservation of patient data to present a complete clinical history

Frequently Asked Questions


Filters

Predictive Analytics Software in Healthcare and Life Sciences

  • 3.6
    5 Reviews

    SPSS Modeler reduces the complexities involved in the transformation of data by providing easy-to-use models. SPSS Modeler is extensively used across various languages to analyze data from multiple databases. It majorly helps in analyzing data to predict customer churn rates and data sets. The application can be used across various industry verticles.

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    • Enterprise
    • New York, USA
    • Founded: 1911
    • $50BN to $100BN
    • 1,00,001 to 5,00,000
  • 3.55
    5 Reviews

    Rapid Miner Studio enables users to create complex predictive models by using a drag and drop visual interface. It has a library of 1500+ machine learning algorithms and functions that can be used to build models specific to any situation. It also offers templates for common cases such as prediction of customer churn, fraud detection, predictive maintenance, etc. It provides proactive recommendations at each step for guidance. Rapidminer helps increase productivity across teams.

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    • SME
    • Massachusetts, USA
    • Founded: 2006
    • $11MN to $50MN
    • 51 to 100
  • 3.37
    3 Reviews

    ORACLE Analytics Cloud’s Database Platform allows the use of seamless predictive analytics software within the platform, giving it an edge over other vendors. ORACLE Analytics Cloud helps mine various data types, eradicate movement of data, and deliver actionable insights. Application developers deploy this analytics model along with SQL and R functions. ORACLE Analytics Cloud helps predict the behavior of customers, the gap between the demand and supply, and make better marketing strategies.

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    • Enterprise
    • California, USA
    • Founded: 1977
    • $10BN to $50BN
    • 1,00,001 to 5,00,000
  • 3.35
    6 Reviews

    SAP Predictive Analytics software enables users to create, deploy and maintain various predictive models. These on-premise tools can help users anticipate future behavior and outcomes and better guide the decision-making ability to help grow the business. SAP Predictive Analytics Cloud works alongside the BI and planning tools to visualize, plan and predict context. The tool uses in-memory technology and machine learning to uncover relevant predictive insights in real-time.

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    • Enterprise
    • Weinheim, Germany
    • Founded: 1972
    • $10BN to $50BN
    • 75,001 to 1,00,000
  • 3.25
    5 Reviews

    Angoss uses data and predictive modeling to present insights that help users make better decisions faster. It uses advanced statistical algorithms for the prediction of outcomes. These outcomes are generated across all stages of model cycles. It helps improving predictive analytics for organizations looking to monetize their data.

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    • SME
    • Michigan, USA
    • Founded: 1985
    • $101MN to $500MN
    • 1,001 to 5,000
  • 3.23
    3 Reviews

    SAS Advanced Analytics provides users with better response time and faster insights provided by its in-memory analytics. SAS Advanced Predictive Analytics software helps organize data in a structured manner, making it easy to understand and present. It enables the user to analyze past, present, and future models using quality-tested algorithms. Automation of large-scale forecasts is also possible without the need for high levels of technical knowledge.

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    • Enterprise
    • North Carolina, USA
    • Founded: 1976
    • $1BN to $5BN
    • 10,001 to 15,000
  • 3.19
    2 Reviews

    Use the full potential of information to unleash the capability of the human resources of an organization.

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    • Enterprise
    • California, USA
    • Founded: 2003
    • $1BN to $5BN
    • 1,001 to 5,000
  • 2.99
    4 Reviews

    Information Builders WebFocus RStat is a cost-effective, robust, intuitive, and accurate predictive analytics software. WebFocus can help organizations by extracting meaningful insights from data of any kind. It creates interactive dashboards to consolidate information which increases the chances of actionable insights to be used in the everyday conduct of data-driven businesses.

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    • SME
    • New York, USA
    • Founded: 1975
    • $101MN to $500MN
    • 1,001 to 5,000
  • 2.96
    5 Reviews

    FICO Decision Management Suite is an integrated environment for development that is compatible with web as well as mobile applications. It is a platform that handles real-time streaming of data including its visualization, indexing, search, and pre-processing, based on rules that are defined in advance. The company's USP is the ability to provide models based on precise customer requirement to reduce time and cost.

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    • Enterprise
    • California, USA
    • Founded: 1956
    • $500MN to $1BN
    • 1,001 to 5,000
  • 2.86
    2 Reviews

    Alteryx provides information science that can viably and productively tap into a code-free and code-accommodating easy-to-use application. The predictive analytics software requires no coding, however, it is coding friendly for those interested. It has a fantastic interface without code for both analytics modelling and advanced modelling with code. It enables easy deployment and management of analytic models, flexibility, agility, and high speed. It supports visualization tools and all data sources. Alteryx helps find, manage, and understand all sort of analytic information of an organization at a high speed, thereby making better decisions and increasing productivity.

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    • SME
    • California, USA
    • Founded: 1997
    • $101MN to $500MN
    • 501 to 1,000
  • 2.78
    4 Reviews

    MicroStrategy’s features and algorithms provide enterprises with advanced predictive analytics capabilities. MicroStrategy is useful for deploying models with governed data. It integrates seamlessly with R and can be connected to any source with the use of APIs. Some of its important features include: Scalable integration with R, incorporation of statistics, ARIMA, etc. and minimal IT support required

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    • SME
  • 2.7
    3 Reviews

    Rapid assembling of predictive data that changes crude information into a business affecting service. This product has advantages for all types of users: analytics leaders, data scientists, IT professionals, and business analysts. It helps analytics leaders in terms of managing productivity, collaboration, coordination, and measuring team growth. Data scientists benefit in terms of automation, modelling, flexibility, and reproducibility. IT professionals gain advantages pertaining to scalability, code & integration, operationalization, and data governance; while business analysts obtain data access, preparation, exploration, and automated ML benefits.

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    • Startup
    • New York, US
    • Founded: 2013
    • $11MN to $50MN
    • 101 to 500
  • 2.69
    3 Reviews

    Extensive set of cloud services that enables associations to address business problems, construct, oversee, and convey applications on a massive, worldwide system utilizing various tools and frameworks. Microsoft Azure ML Studio can be used to prepare and manage the data they need for machine learning. It can improve productivity through its powerful capabilities that can integrate the current model cycle with that of the app lifecycle.

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    • Enterprise
    • Washington, USA
    • Founded: 1975
    • More than $100 BN
    • 1,00,001 to 5,00,000
  • 2.61
    1 Reviews

    GoodData is a cloud-based platform with high SLA availability and maintenance. It allows for easy incorporation of already existing data warehouses. It allows the platform to be integrated into web or mobile applications. It is one of the most dominant cloud data warehouse that meets most versatile analytics platform requirements.

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    • SME
    • California, USA
    • Founded: 2007
    • $11MN to $50MN
    • 101 to 500
  • 2.61
    3 Reviews

    Natural language search and AI-powered bits of knowledge discovery make creating bits of knowledge a characteristic, instinctive, and intuitive experience. Spotfire has strong built-in predictive analytical methods that are smart, yet easy to use. Its intelligent data wrangling helps you clean and modify data, and auto-records it so you can edit it later as well. It is flexible and can scale secured documents as well.

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    • Enterprise
    • California, USA
    • Founded: 1997
    • $1BN to $5BN
    • 1,001 to 5,000
  • 2.44
    2 Reviews

    NTT Data offers effective solutions that supplement the decision-making process in an organization. This is possible across multiple business platforms and across different development and deployment capabilities. With the help of a comprehensive analytics and business insight methodology, NTT Analytics Solutions can change a client organization into an information-driven pioneer.

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    • Enterprise
    • 1,00,001 to 5,00,000
  • 2.39
    2 Reviews

    Teradata predictive analytics software provides “Flip the Switch” analytics which allows on-the-fly switching of best campaign users from reverse modeling to forward prediction. Teradata Analytics for Enterprise Applications eradicates the complexity of enterprise application integration, delivers real-time access to integrated data from ERP and other enterprise applications, as well as provides transparency and visibility into business and customer insights.

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    • Enterprise
    • California, USA
    • Founded: 1979
    • $1BN to $5BN
    • 10,001 to 15,000
  • 2.23
    2 Reviews

    KNIME is an open source software and it helps create data science applications and services. Being open, intuitive, and able to integrate new developments, this platform makes reusable components accessible to all the users and helps understand data science workflows. The software provides actual data analysis as well as a number of processes and has productivity funtions to help operations.

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    • SME
    • Zurich, Switzerland
    • Founded: 2008
    • Below $10 MN
    • 1 to 50
  • 2.05

    Sisense makes the analytics process easy for users right from the preparation of data to the creation of insights. Sisense is an intelligence software known for its agility and easy implementation. It can be used by varied companies. This platform offers a range of business analytics features. It is designed to make complex data preparation and visualizations simple to make better business decisions and intelligent strategies.

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    • SME
    • New York, USA
    • Founded: 2004
    • $101MN to $500MN
    • 501 to 1,000
  • 2.01
    3 Reviews

    Cloud-based Predictive Intelligence is used to generate insights into the behavior of customers and provides recommendations based on these insights to enhance revenue generation. Delivers reliable and customized experiences over each interaction point through a flexible, adaptable, and versatile stage that addresses enterprise needs.

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    • SME
    • California, USA
    • Founded: 2006
    • $11MN to $50MN
    • 101 to 500
  • 1.91

    Domino delivers predictive models using ML and AI techniques capturing all the dependencies of experiments. It is perfect for models across cloud databases as well as distributed systems. Powering model-driven organizations to rapidly create and convey models that drive business impact.

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    • Startup
    • California, USA
    • Founded: 2013
    • $11MN to $50MN
    • 101 to 500

Reviews

Head - Product Management,Company Name Classified
Head - Product Management, Company Name Classified
(*)(*)(*)(*)(*)5

“Predictive Analytics Software"

The platform provides a personalized shopping experience. It has an in-store mode for mobile applications that has impressive features like highlighting store-specific features when a customer enters a brick-and-mortar shop.
Head - Product Management,Company Name Classified
Head - Product Management, Company Name Classified
(*)(*)(*)(*)(*)5

“Best e-commerce platform"

It has pre-built e-commerce integrations that speed up marketing with both android and apple mobile apps.
Technical Director,Company Name Classified
Technical Director, Company Name Classified
(*)(*)(*)(*)(*)5

“Powerful market research"

The software provides extended documentation that is readily available to every user. This support from the software has helped me make market researches quite powerful to stand firm even with customized projects for competing in the market. 
Technical Director,Company Name Classified
Technical Director, Company Name Classified
(*)(*)(*)(*)(*)5

“Faster and cleaner"

With Q Research, everything is so easy and quick. Be it data transforming, cleaning, designing, analysis, or even outputs, this tool has made everything very automatic, clean, and fast compared to other similar tools or software. 
General Manager,Company Name Classified
General Manager, Company Name Classified
(*)(*)(*)(*)( )4

“Good Graphics"

Comfortable, intuitive working environment, with help during the development of the process. Good graphics, and options to visualize the result of the process
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